Performance of R-Tree with Slim-Down and Reinsertion Algorithm

With the development of information technology, the amount of the multimedia data become more and more. The growth of these data brings the need for more effective methods in retrieval. The multimedia retrieval systems always index these data on the basis of feature vectors. In order to handle these vectors efficiently, the index structures such as the R-tree family are used to manage them. Slim-down algorithm is used in Slim-tree, and it can improve the number of disk accesses for range queries in average 10%-20% for vector datasets. Especially for datasets with bigger bloat-factors, the average improvement rise to 25%-35%. In this paper, we use Slim-down algorithm in R-tree index structure to test whether it´s efficient in rectangle node management, and compare it with Reinsertion algorithm. The experiment results show that the Slim-down algorithm is not suitable for reducing the intersection of rectangle regions as it do to the Slim-tree nodes. It can not improve the performance of R-tree distinctly.